Search Results for "software metrics"
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Showing 34 open source projects for "software metrics"
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Best-of Web Development with Python
A ranked list of awesome python libraries for web development
This curated list contains 570 awesome open-source projects with a total of 2.4M stars grouped into 26 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from Github and different package managers. If you like to add or update projects, feel free to open an issue, submit a pull request, or directly edit the projects.yaml. Contributions are very welcome! A ranked list of awesome python libraries for web development... -
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Best-of Machine Learning with Python
A ranked list of awesome machine learning Python libraries
This curated list contains 900 awesome open-source projects with a total of 3.3M stars grouped into 34 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an issue, submit a pull request, or directly edit the projects.yaml. Contributions are very welcome! General-purpose machine learning and deep learning frameworks. -
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PyMuPDF
Python bindings for MuPDF's rendering library.
MuPDF is a lightweight PDF, XPS, and E-book viewer. MuPDF consists of a software library, command line tools, and viewers for various platforms. The renderer in MuPDF is tailored for high-quality anti-aliased graphics. It renders text with metrics and spacing accurate to within fractions of a pixel for the highest fidelity in reproducing the look of a printed page on the screen. The viewer is small, fast, yet complete. It supports many document formats, such as PDF, XPS, OpenXPS, CBZ, EPUB... -
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GDScript Toolkit
Independent set of GDScript tools - parser, linter and formatter
Independent set of GDScript tools, parser, linter and formatter. This project provides a set of tools for daily work with GDScript. At the moment it provides a parser that produces a parse tree for debugging and educational purposes. A linter that performs a static analysis according to some predefined configuration. A formatter that formats the code according to some predefined rules. A code metrics calculator which calculates the cyclomatic complexity of functions and classes. To install... -
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django-prometheus
Export Django monitoring metrics for Prometheus.io
Export Django monitoring metrics for Prometheus.io. This library provides Prometheus metrics for Django-related operations. Prometheus uses Histogram based grouping for monitoring latencies. You can define custom buckets for latency, adding more buckets decreases performance but increases accuracy. SQLite, MySQL, and PostgreSQL databases can be monitored. Just replace the ENGINE property of your database, replacing django.db.backends with django_prometheus.db.backends. You may want to monitor... -
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DIG
A library for graph deep learning research
... your own methods within our extensible framework, and compare with current baseline methods using common datasets and evaluation metrics without extra efforts. It includes unified implementations of data interfaces, common algorithms, and evaluation metrics for several advanced tasks. Our goal is to enable researchers to easily implement and benchmark algorithms. -
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Robusta
Kubernetes observability and automation
Keep your Kubernetes microservices up and running. Connect your existing Prometheus, gain 360° observability. Robusta is both an automation engine for Kubernetes and a multi-cluster observability platform. Robusta is commonly used alongside Prometheus, but other tools are supported too. By listening to all the events in your cluster, Robusta can tell you why alerts fired, what happened at the same time, and what you can do about it. Robusta can either improve your existing alerts or be used... -
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Best-of Python Developer Tools
A ranked list of awesome python developer tools and libraries
A ranked list of awesome Python developer tools and libraries. Updated weekly. This curated list contains 270 awesome open-source projects with a total of 810K stars grouped into 16 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an issue, submit a pull request, or directly edit the projects.yaml. Contributions... -
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DVC
Data Version Control | Git for Data & Models
DVC is built to make ML models shareable and reproducible. It is designed to handle large files, data sets, machine learning models, and metrics as well as code. Version control machine learning models, data sets and intermediate files. DVC connects them with code and uses Amazon S3, Microsoft Azure Blob Storage, Google Drive, Google Cloud Storage, Aliyun OSS, SSH/SFTP, HDFS, HTTP, network-attached storage, or disc to store file contents. Version control machine learning models, data sets... -
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Kornia
Open Source Differentiable Computer Vision Library
Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within... -
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DefectDojo
DefectDojo is a DevSecOps and vulnerability management tool
... with JIRA to manage vulnerabilities in developer's natural backlogs. DefectDojo has smart features that learn over time and can automatically tune results. DefectDojo has everything you need to track projects, personnel, metrics, and tasks. DefectDojo allows you to focus on what you actually enjoy doing, rather than reports and metrics. -
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smclarify
Fairness aware machine learning. Bias detection and mitigation
... that returns a bias metric. A bias metric is a numerical value indicating the level of bias detected as determined by a particular bias measure. A collection of bias metrics for a given dataset or a combination of a dataset and model. -
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Recommenders 2023
Best Practices on Recommendation Systems
Recommenders objective is to assist researchers, developers and enthusiasts in prototyping, experimenting with and bringing to production a range of classic and state-of-the-art recommendation systems. Recommenders is a project under the Linux Foundation of AI and Data. -
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SDGym
Benchmarking synthetic data generation methods
... the SDV project, or input your own data. Choose from any of the SDV synthesizers and baselines. Or write your own custom machine learning model. In addition to performance and memory usage, you can also measure synthetic data quality and privacy through a variety of metrics. Install SDGym using pip or conda. We recommend using a virtual environment to avoid conflicts with other software on your device. -
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Sonnet
TensorFlow-based neural network library
Sonnet is a neural network library built on top of TensorFlow designed to provide simple, composable abstractions for machine learning research. Sonnet can be used to build neural networks for various purposes, including different types of learning. Sonnet’s programming model revolves around a single concept: modules. These modules can hold references to parameters, other modules and methods that apply some function on the user input. There are a number of predefined modules that already... -
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PyTorch Lightning
The lightweight PyTorch wrapper for high-performance AI research
.... When you need to scale up things like BERT and self-supervised learning, Lightning responds accordingly by automatically exporting to ONNX or TorchScript. PyTorch Lightning can easily be applied for any use case. With just a quick refactor you can run your code on any hardware, run distributed training, perform logging, metrics, visualization and so much more! -
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xTuring
Easily build, customize and control your own LLMs
xTuring is an open-source AI personalization software. xTuring makes it easy to build and control LLMs by providing a simple interface to personalize LLMs to your own data and application. xTuring provides fast, efficient and simple fine-tuning of LLMs, such as LLaMA, GPT-J, Galactica, and more. By providing an easy-to-use interface for fine-tuning LLMs to your own data and application, xTuring makes it simple to build, customize and control LLMs. The entire process can be done inside your... -
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PowerfulSeal
A powerful testing tool for Kubernetes clusters.
PowerfulSeal injects failure into your Kubernetes clusters so that you can detect problems as early as possible. It allows for writing scenarios describing complete chaos experiments. -
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speedtest-cli
Command line interface for testing internet bandwidth using speedtest
... connection performance metrics like download, upload, latency and packet loss natively without relying on a web browser. Test the internet connection of your Linux desktop, a remote server or even lower-powered devices such as the Raspberry Pi with the Speedtest Server Network. Set up automated scripts to collect connection performance data, including trends over time. -
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TFLearn
Deep learning library featuring a higher-level API for TensorFlow
TFlearn is a modular and transparent deep learning library built on top of Tensorflow. It was designed to provide a higher-level API to TensorFlow in order to facilitate and speed up experimentations while remaining fully transparent and compatible with it. Easy-to-use and understand high-level API for implementing deep neural networks, with tutorials and examples. Fast prototyping through highly modular built-in neural network layers, regularizers, optimizers, and metrics. Full transparency... -
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Metrix++
Management of source code quality is possible.
The project has been moved to https://github.com/metrixplusplus/metrixplusplus ______________________ Metrix++ is an extendable tool to collect and analyse code metrics. - Multiple languages supported - Multiple metrics available - Configurable. Every metric has got 'turn-on' and other configuration options. There are no predefined thresholds for metrics or rules. You can choose and configure any limit you want. - High-performance. Processes thousands of files per minutes. - Seamless... -
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Ouroboros
Automatically update running docker containers
... and redeploy your container autonomously. Notify you via many platforms courtesy of Apprise. Serve metrics for trend monitoring (Currently: Prometheus/Influxdb) Per-command and scenario examples can be found in the wiki. -
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PyTorch Natural Language Processing
Basic Utilities for PyTorch Natural Language Processing (NLP)
PyTorch-NLP is a library for Natural Language Processing (NLP) in Python. It’s built with the very latest research in mind, and was designed from day one to support rapid prototyping. PyTorch-NLP comes with pre-trained embeddings, samplers, dataset loaders, metrics, neural network modules and text encoders. It’s open-source software, released under the BSD3 license. With your batch in hand, you can use PyTorch to develop and train your model using gradient descent. For example, check out... -
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GreenHop
Energy and environmental monitoring of the server room
The solution GreenHop aims to perform energy and environmental (temperature, humidity, dew point and atmospheric pressure) monitoring of the Data Center server room, providing energy efficiency indicators through green metrics for Data Centers. The GreenHop solution is based on open source software and hardware. The approach of using open source solutions enables its deployment easier and independently of suppliers at the same time makes the solution scalable to the needs of each... -
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Kaengu
kaengu: Framework to build C-Code Flow Graphs and to calculate Metrics
Kaengu is a framework to build Code Flow Graphs from C-Source Code and to calculate different metrics. Graphical view on Code is a strong tool to a.) understand software and b.) detect flaws. Additionally, Kaengu can calculate some interesting metrics, such as the newly developed F-Complexity as well as Graph energy and propositions for Code Refactoring.